ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00350485" target="_blank" >RIV/68407700:21240/21:00350485 - isvavai.cz</a>

Výsledek na webu

<a href="https://ojs.aaai.org/index.php/AAAI/article/view/17997" target="_blank" >https://ojs.aaai.org/index.php/AAAI/article/view/17997</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding

Popis výsledku v původním jazyce

We present ESO-MAPF, a research and educational platform for experimenting with multi-agent path finding (MAPF). ESO-MAPF focuses on demonstrating the planning-acting chain in the MAPF domain. MAPF is the task of finding collision free paths for agents from their starting positions to given individual goals. The standard MAPF uses the abstraction where agents move in an undirected graph via traversing its edges in discrete steps. The discrete abstraction simplifies the planning phase however resulting discrete plans often need to be executed in the real continuous environment. ESO-MAPF shows how to bridge discrete planning and the acting phase in which the resulting plans are executed on physical robots. We simulate centralized plans on a group of OZOBOT Evo robots using their reflex functionalities and outputs on the surface of the screen that serves as the environment. Various problems arising along the planning-acting chain are illustrated to emphasize the educational point of view.

Název v anglickém jazyce

ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding

Popis výsledku anglicky

We present ESO-MAPF, a research and educational platform for experimenting with multi-agent path finding (MAPF). ESO-MAPF focuses on demonstrating the planning-acting chain in the MAPF domain. MAPF is the task of finding collision free paths for agents from their starting positions to given individual goals. The standard MAPF uses the abstraction where agents move in an undirected graph via traversing its edges in discrete steps. The discrete abstraction simplifies the planning phase however resulting discrete plans often need to be executed in the real continuous environment. ESO-MAPF shows how to bridge discrete planning and the acting phase in which the resulting plans are executed on physical robots. We simulate centralized plans on a group of OZOBOT Evo robots using their reflex functionalities and outputs on the surface of the screen that serves as the environment. Various problems arising along the planning-acting chain are illustrated to emphasize the educational point of view.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA19-17966S" target="_blank" >GA19-17966S: intALG-MAPFg: Inteligentní algoritmy pro zobecněné varianty multi-agetního hledání cest</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence

ISBN

978-1-57735-866-4

ISSN

2159-5399

e-ISSN

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Počet stran výsledku

3

Strana od-do

16014-16016

Název nakladatele

AAAI Press

Místo vydání

Menlo Park

Místo konání akce

Virtual

Datum konání akce

2. 2. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000681269807198